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  • CN 62-1070/P
  • ISSN 1000-694X
  • 双月刊 创刊于1981年
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沙漠与沙漠化

基于主成分分析法的戈壁地表砾石粒径遥感估测模型研究

  • 姚爱冬 ,
  • 曹晓阳 ,
  • 冯益明
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  • 中国林业科学研究院 荒漠化研究所, 北京 100091
姚爱冬(1989-),男,山东潍坊人,硕士研究生,主要从事遥感技术应用研究。Email:aidongyao@163.com

收稿日期: 2013-10-29

  修回日期: 2013-12-11

  网络出版日期: 2014-09-20

基金资助

国家自然科学基金项目(31370708)资助

Remote-sensing Model for Estimating the Size of Gobi Surface Gravel Based on Principal Components Analysis

  • Yao Aidong ,
  • Cao Xiaoyang ,
  • Feng Yiming
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  • Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China

Received date: 2013-10-29

  Revised date: 2013-12-11

  Online published: 2014-09-20

摘要

戈壁地表砾石粒径与遥感多光谱数据、植被指数及地学因子存在相关关系,但这些因子间可能存在着多重相关性,如利用这些因子直接建模估测戈壁地表砾石粒径,则可能出现病态模型。利用主成分分析法筛选因子,既可保留多个相关因子的主要信息,又可避免因子间共线性的问题,达到降维、简化模型的效果。因此,本文以新疆哈密市境内山前洪积扇戈壁地表砾石为研究对象,以2010年Landsat TM遥感影像及30 m分辨率DEM为基本数据源,采用主成分分析法,从选择的43个遥感及地学因子(主要包括影像各波段信息、DEM、NDVI、 GEMI,影像经K-T变换得到SBI、GVI、WVI三个分量,通过纹理分析得到的各个波段的均值、方差、信息熵、相关性及对比度等纹理因子,以及利用DEM提取的粗糙度等)中,筛选提取其主成分。结果表明,第一主成分至第五主成分的累计贡献率达98.0%,以前5个主成分作为自变量,借助SPSS软件中的多元回归分析功能,建立戈壁地表砾石粒径估测的回归模型,模型经方差分析及相关性检验,达到显著相关水平。基于建立的估测模型,进行了戈壁地表砾石粒径估测,经验证,实测值与估算值紧密相关。研究可帮助我们了解戈壁的特征,为戈壁区改造利用,认识沙粒迁移、沙漠扩展提供技术支持。

本文引用格式

姚爱冬 , 曹晓阳 , 冯益明 . 基于主成分分析法的戈壁地表砾石粒径遥感估测模型研究[J]. 中国沙漠, 2014 , 34(5) : 1215 -1221 . DOI: 10.7522/j.issn.1000-694X.2013.00362

Abstract

The size of gobi surface gravel is correlated to the factors such as multispectral remote sensing data, vegetation indexes and geological factors. However, these factors are usually strongly correlative. The size of gobi surface gravel model will become an ill-posed one if the model is built directly with the factors. The principal components (PCs) for those factors are obtained by principal components analysis (PCA). In that case, not only the main information of these factors can be reserved in the model, the multicolliearity problem of the factors can also be avoided. Moreover, the number of the variables decreases and the model is optimized. Based on the data obtained from Landsat TM images of 2010 and 30 m DEM at a alluvial-fan in Hami, Xinjiang, China, the paper analyzes the PCs by PCA for the 43 factors, which include 6 multi-spectral bands, 2 kinds of vegetation index of NDVI and GEMI, surface roughness generated from DEM, mean, variance, entropy, correlation and contrast extracted from texture analysis. The results show that the accumulative ratio of contribution of the first 5 PCs is 98.0%. Then the size of gobi surface gravel model is set up by regression analysis of SPSS 18 based on these first 5 PCs. F test examination shows that the size of gobi surface gravel is correlated significantly to these first 5 PCs. Finally, the study estimates the size of gobi surface gravel based on the model, and the precision is above 80%. We could learn about the gobi characteristics, cognize the laws of sand grain move and desert extension by studying the grain size of gobi surface gravel.

参考文献

[1] 冯益明,吴波,周娜,等.基于遥感影像识别的戈壁分类体系研究[J].中国沙漠,2013,33(3):635-641.
[2] 国家林业局.中国荒漠化和沙化状况公报[R].2011.
[3] 王涛,陈广庭.西部地标:中国的沙漠、戈壁[M].上海:上海科学技术文献出版社,2008:216-224.
[4] M.Π.彼得罗夫著.世界荒漠[M].胡孟春,李耀明,译.北京:中国环境科学出版社,2010:5-18.
[5] Π.格拉西莫夫,王乃樑,陈静生,等.戈壁荒漠[J].地理学报,1955,21(2):129-140.
[6] 屈建军,张克存,张伟民,等.几种典型戈壁床面风沙流特性比较[J].中国沙漠,2012,32(2):285-290.
[7] 冯益明,智长贵,姚爱冬.基于决策树的戈壁信息提取研究[J].干旱区地理,2013,36(3):1-6.
[8] 薛娴,张伟民,王涛.戈壁砾石防护效应的风洞实验与野外观测结果——以敦煌莫高窟顶戈壁的风蚀防护为例[J].地理学报,2000,55(3):375-383.
[9] 董治宝,屈建军,刘小平,等.戈壁表面阻力系数的实验研究[J].中国科学(D辑),2001,31(11):954-958.
[10] Xiao J Y,Shen Y J,Ryutaro T. Mapping soil degradation by topsoil grain size using MODIS data [EB/OL]. 2005.http://www2.cr.chibau.jp/symp2005/documents/Postersession/p003_Jieyingxiao_paper.pdf.
[11] Salisbury J W,D'Aria D M.Infrared (8-14 μm)remote sensing of soil particle size[J].Remote Sensing of Environment,1992,42:157-165.
[12] 罗乔顺.基于土地利用/覆盖变化的哈密地区遥生态经济可持续发展研究[D].乌鲁木齐:新疆农业大学,2008.
[13] 刑文渊,肖继东,师庆东,等.哈密地区绿洲植被遥感监测及其变化原因分析[J].草业科学,2007,24(9):34-37.
[14] 邓书斌.ENVI遥感图像处理方法[M].北京:科学出版社,2012:104-105.
[15] Kauth R J,Thomas G S. The tasseled cap- a graphic description of the spectral-temporal development of agricultural crops as seen by landsat[C]//Proceedings of symposium on machine processing of remotely sensed data.West Lafayette,USA:Laboratory for Applications of Remote Sensing,1976.
[16] 洪奕丰,严恩萍,林辉,等.浙江地貌形态与土地覆盖格局关系的研究[J].中南林业科技大学学报,2012,32(3):63-69.
[17] 邓书斌,武红敢,江涛.基于PCA/NDVI的森林覆盖遥感信息提取方法研究[J].国土资源遥感,2007,72(2):82-85.
[18] 徐文科,蔡体久,琚存勇.基于RS和GIS的毛乌素沙地荒漠化程度定量估测[J].林业科学,2007,43(5):48-53.
[19] 徐天蜀,张王菲,岳彩荣.基于PCA的森林生物量遥感信息模型研究[J].生态环境,2007,16(6):1759-1762.
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